UK insurers face ‘data quality’ obstacles in AI adoption
British insurers are facing a bigger AI obstacle than expected, as poor quality data is preventing underwriters from accelerating adoption.
A new report by tech firm CI&T, in collaboration with Reuters Events, revealed that nearly three-quarters (72 percent) of underwriters identified fragmented and unstructured data as the primary barrier to AI transformation.
The next top challenge was accurate risk assessment, cited by 42 percent, and pricing accuracy, cited by 36 percent of the respondents.
Mike Young, vice-president of insurance industry growth at CI&T said: “AI’s success in insurance won’t be determined by how advanced the algorithms are, but by the quality and accessibility of the data that feeds them.”
Insurers ready to innovate
Respondents, including insurance professionals from the UK, identified the biggest threat to insurers optimizing data as the difficulty of extracting, analysing, and utilising unstructured data, which was cited by 54 percent of the professionals.
While 24 per cent highlighted issues around consolidating multiple data sources into data lakes and warehouses, and a further 14 per cent cited data literacy of employees as an issue.
As a result, the high cost of acquiring relevant data and inefficiencies in its usage within the insurance process lead to higher costs for underwriting agencies compared to carriers.
This comes as 60 per cent of respondents believe AI-led efficiency will be crucial to offset rising claim costs and premiums. As Young noted, “Claims inflations peaked at 12 per cent in 2023 and is expected to remain a top risk for UK insurers in 2025 across property, casualty, and motor lines, so the increased interest in tech to increase cost efficiency is no surprise.”
He added: “This research shows UK insurers are ready to innovate, but they need to get their data house in order first.”